eprintid: 380
rev_number: 6
eprint_status: archive
userid: 5
dir: disk0/00/00/03/80
datestamp: 2011-07-11
lastmod: 2013-06-28 14:23:37
status_changed: 2013-06-28 14:23:37
type: techreport
metadata_visibility: show
item_issues_count: 0
creators_name: Rocca, Paolo
creators_name: Benedetti, Manuel
creators_name: Donelli, Massimo
creators_name: Massa, Andrea
title: Evolutionary Techniques For Inverse Scattering: Current Trends and Envisaged Developments
ispublished: pub
subjects: TU
full_text_status: public
note: This version is a pre-print of the final version available at IEEE.
abstract: The possibility of sensing a given region from the measurements of the scattered field when it is illuminated through low-power microwave electromagnetic waves is still a topic of great interest due to the wide range of applications in many different areas of medical, industrial, and civil engineering. For instance, let us consider problems related to biomedical engineering, non-invasive thermometry, non-destructive testing and evaluation, geophysical analysis, remote sensing, and archeology. Although this list is certainly non-exhaustive, it is sufficient to justify the great attention devoted to the solution of inverse scattering problems both from a theoretical and algorithmic point of view, as demonstrated by the large amount of papers and books available in the scientific literature. The issues that actually limit the proliferation of practical imaging systems are the intrinsic theoretical difficulties (i.e., ill-posedness and non-linearity), which characterize an inverse scattering problem. The ill-posedness can be avoided by using additional (a-priori) information directly taken from the physics of the problem at hand. This strategy allows one to avoid the reconstruction of artifacts and obtain the so-called regularized solutions. Concerning the non-linearity of the inverse scattering model, it must be considered to take into account the multiple-scattering effects, since linear approximations (e.g., Born-like approaches) can be rarely applied to real objects. Accordingly, many non-linear inversion techniques have been proposed for the optimization of a suitable cost function taking into account the mismatch between the measured data and the reconstructed ones. Originally, various deterministic approaches based on steepest-descent algorithms [e.g., conjugate-gradients (CG)] were proposed [1]. Although they have shown to provide successful results, they suffer the presence of local minima when initial solution does not belong to the “attraction basin” of the global optimum.
date: 2011-01
date_type: published
institution: University of Trento
department: informaticat
refereed: FALSE
referencetext: [1] P. M. Van den Berg and A. Abubakar, “Contrast source inversion method: state of the art,” PIER, vol. 34, pp. 189-218, 2001. [2] L. Garnero et al., “Microwave imaging-complex permittivity reconstruction-by simulated annealing,” IEEE Trans. Microwave Theory Tech., vol. 39, pp. 1801–1807, 1991. [3] A. Massa et. al., “Improving the effectiveness of GA-based approaches to microwave imaging through an innovative parabolic crossover,” IEEE Antennas Wireless Propag. Lett., vol. 4, pp. 138-142, 2005. [4] A. Massa et al., “A computational technique based on a real coded genetic algorithm for microwave imaging purposes,” IEEE Trans. Geosci. Remote Sens., vol. 38, no. 4, pp. 1697-1708, Jul. 2000. [5] A. Massa et al., “Parallel GA-based approach for microwave imaging applications,” IEEE Trans. Antennas Propag., vol. 53, no. 10, pp. 3118-3127, Oct. 2005. [6] M. Donelli et al., “An integrated multiscaling strategy based on a particle swarm algorithm for inverse scattering problems,” IEEE Trans. Geosci. Remote Sens., vol. 44, no. 2, pp. 298-312, Feb. 2006. [7] M. Donelli et al., “Three-dimensional microwave imaging problems solved through an efficient multiscaling particle swarm optimization,” IEEE Trans. Geosci. Remote Sens., accepted for publication. [8] M Donelli and A. Massa, “A computational approach based on a particle swarm optimizer for microwave imaging of two dimensional dielectric scatterers,” IEEE Trans. Microwave Theory Techn., vol. 53, no. 5, pp. 1761?1776, May 2005. [9] M. Brignone et al., “A hybrid approach to 3D microwave imaging by using linear sampling and ACO,” IEEE Trans. Antennas Propag., vol. 56, no. 10, pp. 3224-3232, Oct. 2008. [10] A. Massa et al., “A microwave imaging method for NDE/NDT based on the SMW technique for the electromagnetic field prediction,” IEEE Trans. Instrum. Meas., vol. 55, no. 1, pp. 240-147, Feb. 2006.
citation:   Rocca, Paolo and Benedetti, Manuel and Donelli, Massimo and Massa, Andrea  (2011) Evolutionary Techniques For Inverse Scattering: Current Trends and Envisaged Developments.  [Technical Report]     
document_url: http://www.eledia.org/students-reports/380/1/DISI-11-189.C178.pdf